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40 Algorithms Every Programmer Should Know
book

40 Algorithms Every Programmer Should Know

by Imran Ahmad
June 2020
Intermediate to advanced
382 pages
11h 39m
English
Packt Publishing
Content preview from 40 Algorithms Every Programmer Should Know

Summary

In this chapter, we first looked at the details of neural networks. We started by looking at how neural networks have evolved over the years. We studied different types of neural networks. Then, we looked at the various building blocks of neural networks. We studied in depth the gradient descent algorithm, which is used to train neural networks. We discussed various activation functions and studied the applications of activation functions in a neural network. We also looked at the concept of transfer learning. Finally, we looked at a practical example of how a neural network can be used to train a machine learning model that can be deployed to flag forged or fraudulent documents.

Looking ahead, in the next chapter, we will look into ...

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Publisher Resources

ISBN: 9781789801217Supplemental Content